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You connected to the server, gave it the path to a document, and then the server sent you the contents of that document. It looked like a featureless rip-off of more sophisticated file transfer protocols like FTP. With tongue only slightly in cheek we can say that HTTP is uniquely well suited to distributed Internet applications because it has no features to speak of. In a twist straight out of a kung-fu movie,: the two basic design decisions that made HTTP an improvement on its rivals, and that keep it scalable up to today’s mega-sites.
Many of the features lacking in HTTP 0.9 have since turned out to be unnecessary or counterproductive. Most of the rest were implemented in the 1.0 and 1.1 revisions of the protocol.
We also show you the view from the client side: how you can write programs to consume RESTful services.
Our examples include real-world RESTful services like Amazon’s Simple Storage Service (S3), the various incarnations of the Atom Publishing Protocol, and Google Maps.
It’s time to put the “web” back into “web services.”The features that make a web site easy for a web surfer to use also make a web service API easy for a programmer to use.
To find the principles underlying the design of these services, we can just translate the principles for human-readable web sites into terms that make sense when the surfers are computer programs. Our goal throughout is to show the power (and, where appropriate, the limitations) of the basic web technologies: the HTTP application protocol, the URI naming standard, and the XML markup language.
Note that while we provide as much of the media content as we are able via free download, we are sometimes limited by licensing restrictions.
Today’s “web service” architectures reinvent or ignore every feature that makes the Web successful. We know the technologies behind the Web can drive useful remote services, because those services exist and we use them every day.We say: if the Web is good enough for humans, it’s good enough for robots. Computer programs are good at building and parsing complex data structures, but they’re not as flexible as humans when it comes to interpreting documents.